Politics, Groups, and Identities
ISSN: 2156-5503 (Print) 2156-5511 (Online) Journal homepage: http://www.tandfonline.com/loi/rpgi20
Civic engagement and political participation
among American Indians and Alaska natives in the
US
Kimberly R. Huyser, Gabriel R. Sanchez & Edward D. Vargas
To cite this article: Kimberly R. Huyser, Gabriel R. Sanchez & Edward D. Vargas (2016): Civic
engagement and political participation among American Indians and Alaska natives in the US,
Politics, Groups, and Identities
To link to this article: http://dx.doi.org/10.1080/21565503.2016.1148058
Published online: 18 Feb 2016.
Submit your article to this journal
View related articles
View Crossmark data
Full Terms & Conditions of access and use can be found at
http://www.tandfonline.com/action/journalInformation?journalCode=rpgi20
Download by: [96.42.45.174]
Date: 18 February 2016, At: 16:34
POLITICS, GROUPS, AND IDENTITIES, 2016
http://dx.doi.org/10.1080/21565503.2016.1148058
Civic engagement and political participation among American
Indians and Alaska natives in the US
Kimberly R. Huysera†, Gabriel R. Sanchez † and Edward D. Vargasc†
b
Department of Sociology, University of New Mexico, Albuquerque, NM, USA; bDepartment of Political
Science, University of New Mexico, Political Science, Albuquerque, NM, USA; cCenter for Women’s Health and
Health Disparities Research, University of Wisconsin, Madison, WI, USA
Downloaded by [96.42.45.174] at 16:34 18 February 2016
a
ABSTRACT
ARTICLE HISTORY
Within the growing literature seeking to understand civic and
political engagement among racial and ethnic minorities, our
understanding of political behavior among American Indian and
Alaska Natives (AI/AN) remains limited. We use the Current
Population Survey Civic Engagement and Voting and Registration
supplements (2006–2012) to compare AI/AN voter registration,
voting, and overall civic engagement to other racial and ethnic
groups and to assess whether factors that predict higher levels of
civic engagement vary across these populations. We find a few
key socioeconomic status indicators that predict civic and political
engagement uniquely for AI/ANs, but they are not consistently
significant across all years or all types of political participation. We
find marital status, age, household size, education, and veteran
status to be important in predicting civic engagement for AI/ANs.
However, for voting and registration, we find that family income,
age, marital status, household size, and residential stability to be
important contributors. Although we find AI/ANs are less likely to
register and vote compared to non-Hispanic whites, we find that
the difference is not statistically significant in congressional years,
which may suggest that AI/ANs are engaged in local politics and
vote for representatives who will represent their tribal interests in
national politics.
Received 29 May 2015
Accepted 25 January 2016
KEYWORDS
American Indian; Alaska
native; civic engagement;
political engagement; voting
and registration; quantitative
Introduction
Political participation is arguably the most studied phenomenon within political science,
with a large segment of this vast literature focused on addressing the question of who
engages in the US political system and who does not. With an increase in available data
to make across-group comparisons, there has been a rise in the number of studies
focused on differences in participation across racial and ethnic groups (see Leighley and
Vedlitz 1999; Min 2014; Wong, Lien, and Conway 2005). This work has led to several
general conclusions within the literature, including that racial and ethnic minorities
tend to vote at lower levels than non-Hispanic whites, with a more significant gap
between whites, Latinos, and Asians. Although this area of research is relatively deep
CONTACT Kimberly R. Huyser
[email protected]
†
Names are listed alphabetically and do not reflect contributions made to the project.
© 2016 Western Political Science Association
Downloaded by [96.42.45.174] at 16:34 18 February 2016
2
K. R. HUYSER ET AL.
and continuously growing, our understanding of American Indian and Alaska Native (AI/
AN) political participation remains relatively limited. Our paper intends to shed some
light on this topic by utilizing data from the US Current Population Survey (CPS) to
compare AI/AN voter registration, voting, and overall civic engagement rates to other
racial and ethnic groups. Our analysis contributes to the general knowledge of this important yet often overlooked electorate, but, as we discuss in our conclusion, there remains a
need for more rich data collection that will allow scholars to address several important
questions that are beyond the scope of existing data.
AI/ANs comprise roughly 2% of the overall US population according to the 2012 American Community Survey, with approximately half of that population reporting that they
were AI/AN and some other race. Given the nature of the Electoral College and overall
power of numbers in elections in the US, at first glance, the relatively small population
numbers of this community may lead many to question the relevance of this population
to electoral politics. However, it is important to recognize that this population is concentrated in several states where their political voice is more pronounced (Conner 2014;
Witmer, Johnson, and Boehmke 2014). Peterson (1997) notes that while AI/ANs are
only 2% of the total voting age population, their concentration in states with low population
makes them important political actors. For example, Native voters have more direct influence in New Mexico than in any other state. AI/AN voters in New Mexico represent more
than 9% of eligible voters (over 10% of the overall population), and those percentages are
growing fast because of the relative youth of this population.1 This presence has led to political representation in New Mexico where this community is currently represented in both
chambers of the state legislature. More specifically, there are 2 Native legislators out of 42 in
the state Senate and three Native legislators out of 70 in the New Mexico House. Similarly,
AI/ANs can have a pronounced impact on election outcomes in several other states where
they have a meaningful presence and during a competitive election. This includes Arizona,
Colorado, Alaska, Montana, and the Dakotas, among others.
Furthermore, although the Native American population is relatively small nationally,
given the relative youth of the Native American population (with median age of 31 compared to 37 overall), they are projected to grow to over 11 million in 2060, which would
be nearly 3% of the US population. The need to document and analyze how AI/AN
participation levels compare to other groups is crucial to ameliorate disparities in this
community.
We begin our paper with an overview of the research focused on political participation
among the AI/AN population in the US within the wider political participation literature
that grounds our research design. We then provide a discussion of our data and methods
utilized in our analysis, noting the limitations in data availability for this specific population, followed by our results and conclusions.
AI/AN political participation
Although the literature focused on AI/AN political participation is far more limited than
that focused on other racial and ethnic populations such as Latinos or Asian Americans,
there is an important body of research in this area that we draw from to help inform our
analysis. The formative piece on Native political participation is Peterson’s (1957) American Indian Political Participation. Peterson provides a useful overview of the historical
Downloaded by [96.42.45.174] at 16:34 18 February 2016
POLITICS, GROUPS, AND IDENTITIES
3
political participation of AI/ANs, illustrating that there have been different socio-political
structures governing their societies prior to European arrival in the Americas. Given that
individual tribal members held and exercised rights and responsibilities as members of
those tribes, AI/AN–US government relations have always been carried out in a government-to-government framework. Consequently, Peterson (1957) suggests in his narrative
that many AI/ANs do not follow the traditional individual voting behavior patterns of
most Americans or have strong party affiliations. Instead, they vote according to tribal
issues, often for the candidate who they perceive may advance the best interest of the tribe.
This has been a general finding that has held across more recent studies. For example,
Corntassel and Witmer (1997) support this contention, noting that tribes can influence the
individual votes of their members by endorsing or openly supporting candidates. They
look at the 1994 national elections with a focus on tribes in Arizona and Oklahoma.
Their survey had a response rate of 32% with 19 tribes in total participating in the
study (6 of 21 tribal chairpersons responded which constituted approximately 70% of
the tribal population in the State of Arizona and 13 of 39 tribal chairpersons responded
which was over 50% of the tribal population in the State of Oklahoma). They found
that tribes tend to support those candidates who are more in line with tribal needs and
issues rather than lending support based on cultural ties or party affiliation.
One of the major underlying themes of this literature is the important acknowledgment
that the nature of AI/AN political participation, be it electoral or civic, is influenced by the
unique sovereign status of this population in the US. Benjamin Kahn’s (2013) A Place
Called Home: Native Sovereignty Through Statehood and Political Participation, for
example, looks at the cases of the AI tribes in the US and the Maori in New Zealand.
Kahn argues that political participation in both locations revolves around sovereignty.
While other minority groups often seek inclusion in the legal and socioeconomic framework of the US through participation in civic affairs, AI/ANs may participate in order to
protect and defend their sovereignty rights, including cultural, physical, and legal rights.
Given the potential for different motivations for participation across groups, this provides
the backdrop for a comparison of participation across racial/ethnic groups.
In terms of electoral participation specifically, Peterson (1957) argues that, similar to
other minority groups, historical suppression of AI/AN voting has had an impact on
their current voting trends.2 The Pueblos in New Mexico, for example, suffered from
extremely low voter registration rates in 1952, almost 30 years after all Native Americans
were granted citizenship through the Indian Citizenship Act of 1924 (Pub. L. 68-175, 43
Stat. 253). Only 9 of the 19 Pueblos had any registered voters in 1952! Conversely, and
similar to other minority populations, AI/AN voting increases when states take the initiative to make voting more accessible by eliminating legal barriers (literacy tests, etc.) and
through information and outreach campaigns (Peterson 1957). Peterson (1997) adds to
this argument, noting that historical violence and conflict with the national government
has deeply influenced distrust in the government and affected political participation. Reinforcing the underlying context of inter-group tension, Luna (2000) believes that the socioeconomic conditions of AI/ANs (like high poverty rates and low education attainment) is
compounded by the alienation from national, state, and local power structures that results
from being a widely dispersed population. She points out that historical attempts at exercising electoral rights had been met with hostility and repression against those who
actively sought to engage the Native community in electoral politics.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
4
K. R. HUYSER ET AL.
Unfortunately, AI/ANs have experienced historical discrimination and ongoing barriers that influence the political participation and influence of AI/ANs who live on reservations and within states where reservations are located (McCool, Olson, and Robinson
2007). As one example, South Dakota has a long history of disenfranchising AI/ANs
from voting and holding public office. South Dakota argued that reservation AI/ANs
“do not share the same interest in county government as residents of organized counties”
and thus actively restricted AI/AN voting (Sells 2012). It was not until 1982 that South
Dakota officially ended the disfranchisement of AI/ANs from political engagement
(Sells 2012). In fact, a 2009 report by the American Civil Liberty Union titled “Voting
Rights in Indian Country” makes a connection between historical discrimination and
current political engagement levels by noting that the exclusion of the AI/AN population
from many facets of society has hurt their socioeconomic standing.3
Although the particular laws are no longer in effect, South Dakota continues to have
other discriminatory voting practices and electoral arrangements that deter AI/AN political engagement and participation (Sells 2012). This includes the US Department of Justice
having to intervene just last year in a lawsuit accusing a South Dakota county of disenfranchising Native Americans living on the Pine Ridge Reservation. The lawsuit claimed that
there was no satellite location for voting, forcing citizens living on this reservation to travel
long distances to vote. Similarly, there is speculation that North Dakota’s new photo-ID
law will disproportionately impact Native Americans, as some tribal IDs may not be
valid for voting purposes.4
An important finding from Luna’s (2000) analysis is the difficulty of mobilizing AI/ANs
as a monolithic voting bloc. This is an important finding, as mobilization is one of the key
factors driving political participation (Rosenstone and Hansen 1993), and minority communities have consistently been mobilized at a much lower rate than non-Hispanic whites
(Leighley 2001). This suggests that AI/ANs may have similarities to other racial and ethnic
minorities when it comes to electoral participation and civic engagement. Luna (2000)
notes that the historical politics of colonization destroyed the alliances among tribes
and bands, leading to isolation and focus on the individual survival of the groups. She
writes, “social cohesion among group members is necessary if political mobilization is
to occur.”
“There are deep cleavages between [American] Indian peoples in the United States, separating tribe from tribe, urban from rural, and Western-educated from traditional” (Luna
2000, 102), making lack of cohesion a possible source of relatively low participation rates
among the AI population. Social cohesion is particularly important given the finding that
group identity in the forms of group consciousness and linked fate increases political participation for Latinos and African Americans (Dawson 1994; Sanchez 2006). Internal variation has been found to pose challenges for civic engagement and political participation
among other populations as well, including the pan-ethnic Latino population (see
Beltran 2010). This is another example of similarity between the AI/AN community
and other racial and ethnic minorities that may yield similar civic engagement rates
across these populations.
With limited survey data available for individual-level analysis, we do not have substantial work identifying factors that increase or decrease political participation among AI/
ANs. Peterson (1997) used the 1990 and 1992 CPS, focusing on AI/ANs who were surveyed in the states with the highest AI/AN population: Arizona, Florida, Montana, New
Downloaded by [96.42.45.174] at 16:34 18 February 2016
POLITICS, GROUPS, AND IDENTITIES
5
Mexico, North Dakota, Oklahoma, and South Dakota. In his analysis, he examined how
social demographic indicators such as race, income, gender, and education affect voting
participation in the national elections of 1990 and 1992. These are important factors to
test, as scholars have identified socioeconomic status (income, education, and age) to be
the strongest predictor of who participates in American politics (see Verba, Scholzman
and Brady 1995). In his groundbreaking study, Peterson (1997) found that AI/ANs
were 51% less likely to vote than non-AI/AN respondents and that socioeconomic
status factors did not sufficiently explain AI/AN voting patterns. We therefore approach
our more nationally focused analysis expecting to see similar patterns. That said, given the
more recent nature of our data and the ability to explore both electoral and non-electoral
participation, we may see significant differences from Peterson’s more limited study.
We also hypothesize that serving in the armed forces may be an important mechanism
of political participation for AI/ANs. The Native population has a long-standing tradition
of high levels of representation in the armed forces. For example, Peterson (1957) noted
that 17,000 Native Americans served in World War I, with 85% of those serving in the US
armed forces doing so voluntarily. During World War II, this number increased to more
than 24,000 military personnel. In the more contemporary military, nearly 2% of the 1.4
million active duty military are AI/ANs, with overrepresentation in the Navy and Marines
(Department of Defense 2013; Holiday et al. 2006). Given the propensity for this community to engage in civic affairs through military service, our analysis includes an exploration
of whether political participation varies based on military service.
In summary, the literature in this area has suggested that there may be some synergy
between factors that influence political participation among AI/ANs and the wider racial
and ethnic minority population, including lower rates of mobilization compared to the
non-Hispanic white population. This could lead to similar participation rates for AI/
ANs and other racial and ethnic minorities and common predictor variables in our
models. However, the nature of sovereign status and high internal variation suggest that
some important differences may exist when directly comparing the political participation
rates of AI/ANs to other major racial and ethnic groups. Rather than motivating our
analysis with direct hypotheses, we choose to post these two alternative theoretical expectations that we test in our models. Unfortunately, our analysis will not be able to answer all
of the questions raised in this discussion of the literature such as the differential impact of
group identity on civic engagement. We will, however, be able to use the best nationally
representative data available to identify if there are significant differences in overall
rates of civic engagement and political participation between AI/ANs and other racial
and ethnic groups in the US as well as whether the contributing factors to these
outcome variables vary in any important ways across these populations.
Data and methods
We use the public use CPS November Civic Engagement and Voting and Registration
Supplements to better understand civic engagement and political participation. The
Bureau of the Census for the Bureau of Labor Statistics conducts the CPS monthly in
approximately 56,000 households. We use two of their supplemental surveys for our
analysis (U.S. Census Bureau 2009a, 2009b, 2010a, 2010b). We use two years (2008 and
2010) of the Civic Engagement supplement. Civic engagement is a broad concept that
Downloaded by [96.42.45.174] at 16:34 18 February 2016
6
K. R. HUYSER ET AL.
can be defined by one’s level of or involvement in: empowerment and political action;
groups and networks; trust and solidarity; information and communication; and social
cohesion and inclusion (U.S. Census Bureau 2009a, 2010a). We use four years of the
CPS Voting and Registration supplement to examine voter turnout across both a presidential year (2008 and 2012) and off-year congressional year (2006 and 2010).
Since the Civic Engagement supplement questions have changed slightly between 2008
and 2010 collection years, we use multiple dependent variables to capture civic engagement. These outcomes include: if the respondent contacted a public official, if the respondent boycotted, and the number of the different organizations and groups individuals are
involved in. The different organizations and groups in which individuals participate
include the American Legion or Lions Club, sports clubs, neighborhood or community
organizations such as Parent Teachers Associations or neighborhood watch groups,
church or religious groups, or any other type of organization.
The Voting and Registration supplement has been collected biennially in the November
CPS since 1964, and it does not provide estimates of partisanship, such as what candidate a
voter supported or what political party a voter aligned himself or herself with (U.S. Census
Bureau 2009b, 2010b). The Voting and Registration questions were asked of all persons
who were both US citizens and 18 years of age or older. The CPS instrument determined
who was eligible for the Voting and Registration supplement through the use of check
items that referred to basic CPS items, including age and citizenship. We use two dependent variables within the Voting and Registration Supplement to gauge political participation. The first dependent variable examines whether a respondent voted that election
year. The second gauged political interest through a measure that asks respondents if
they did not register to vote because they were uninterested in politics. Since theoretically
we anticipate that states with concentrations of AI/AN tribal lands or communities will
influence voting patterns of AI/ANs, we have created an Indian state variable that includes
states with the highest AI/AN population: Arizona, Florida, Montana, New Mexico, North
Dakota, Oklahoma, and South Dakota.5 Although county-based analysis would be ideal,
the utilization of AI/AN states has been used by others (Sandefur and McKinnell 1986),
specifically for a study focused on Native American voter turnout (Peterson 1997). Unfortunately, AI/AN county analysis was unavailable because the public use CPS Voting and
Registration only releases counties with populations of 100,000 or more (U.S. Census
Bureau 2010b). Since many tribal lands are located in rural and low-density counties
(Snipp 1989), we are unable to use county-level controls in our analysis and are limited
to state-level analysis. For our voting and registration models, we do adjust for differences
in living in urban or rural areas.
In all of our analyses, we control for individual personal and demographic characteristics. The measures include homeownership, age, marital status, veteran status, employment status, race and ethnicity, gender, family income, education, number of individuals
in the household, and the number of years the respondent lived in their current home. We
also control for whether the respondent was primary interviewee for the household survey.
Analytic strategy
We use logistic regression and negative binomial regression models to examine the
relationship between the host of covariates in our models and our measures of political
POLITICS, GROUPS, AND IDENTITIES
7
participation and civic engagement. For our binary dependent variables, we use logistic
regression to predict (1) whether the respondent is civically or politically engaged, (2)
whether a respondent contacted a public office, (3) reported boycotting, (4) reported
voting, or (5) reported not registering to vote because of lack of interest in politics. We
use negative binomial regression models to specify the number of groups/organizations
respondents are engaged in. We use this categorical data analysis method because we
are interested in capturing the number of times an individual is civically engaged,
which is count data and assumed not to be normally distributed. All statistical analysis
were conducted using Stata 12 software and weighted using the appropriate survey
weight indicators (StataCorp. 2011).
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Results
Table 1 presents the descriptive statistics for both years of the Civic Engagement supplement and Voting and Registration supplement to help provide some context to our
results. Within the Civic Engagement supplement, we see that 11–12% of our full
sample has contacted a public official, and a similar percentage have participated in boycotting activities. Within the Voter and Registration supplement, 72% and 74% of our full
sample in presidential years (2008 and 2012) voted versus 56% in congressional years
(2006 and 2010), reflecting a much lower level of turnout in the off-year races. Across
both years of the Voter and Registration supplement, we have similar prevalence of individuals who did not register to vote due to lack of interest (approximately 47%) and of
respondents who voted by mail (approximately 84%). Among more general characteristics
of our full sample, approximately 63–64% of our sample are homeowners. The average
household size is 2.9 people. The mean age is approximate 47 years, and approximately
51% are female. Approximately 53% are married. Ten percent of our sample are veterans.
The race and ethnic groups in our sample are 75% white, 10% Black, 1% AI/AN, and 13%
Hispanic.
Civic engagement results
We begin our discussion with a comparison of civic engagement rates across race and ethnicity to determine if the AI/AN population participates in these activities to a greater or
lesser extent than other communities. In our unweighted descriptive analysis, we find that
AI/ANs are more civically engaged in boycotting and contacting a public official than
Blacks and Hispanics. AI/ANs have similar rates of political participation to Blacks
(51% versus 54%, respectively). Compared to non-Hispanic whites in 2008, AI/ANs
have similar rates of contacting a public official (11% versus 14%) and lower rates of boycotting and political participation. However, in 2010, AI/ANs are more involved across all
types of civic engagement compared to all other racial and ethnic groups, including whites.
Our results discussion now moves toward analysis of factors that contribute to political
participation with results from the civic engagement models that are presented in
Tables 2–4 highlighting the models focused on AI/ANs. Interestingly, fewer personal
and demographic factors predict AI/AN civic engagement than those for other racial
and ethnic groups. As reflected in Tables 2 and 3, we find that AI/ANs who are
married are more likely to contact a public official (Table 2) and more likely to boycott
8
Table 1. Summary statistics of study sample.
Civic engagement supplement
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Congressional year (2010)
Obs.
Mean
Std. dev.
Obs.
Mean
Std. dev.
Political participation all categories
Civic engagement: contacted public official
Civic engagement: boycott
Homeowner
Incomea
Number in household
Age
Marital status
Female
Veteran
Educationb
Unemployed
Black
AI/AN
White
Hispanic
67,823
68,042
68,005
150,799
110,237
150,799
100,008
105,869
132,812
101,534
105,869
105,416
123,666
123,666
123,666
123,666
0.67
0.12
0.12
0.64
10.89
2.97
46.95
0.54
0.51
0.1
9.95
0.04
0.1
0.01
0.75
0.13
0.96
0.33
0.33
0.48
3.95
1.88
17.52
0.5
0.5
0.3
2.81
0.19
0.31
0.1
0.43
0.34
74,464
74,714
74,580
152,162
134,179
152,162
101,750
107,494
134,179
103,259
107,494
107,082
124,714
124,714
124,714
124,714
0.6
0.12
0.11
0.63
10.63
2.99
47.27
0.53
0.51
0.1
10.01
0.05
0.11
0.01
0.74
0.14
0.92
0.32
0.32
0.48
4.07
1.89
17.63
0.5
0.5
0.3
2.8
0.23
0.31
0.1
0.44
0.35
Voting and registration supplement
Congressional year (2006)
Variable
Voted
Not registered
Voted by mail
Homeowner
Income
Number in household
Age
Marital status
Female
Veteran
Education
Unemployed
Obs.
83,929
16,370
47,055
153,255
113,693
153,255
102,110
108,394
136,046
103,710
108,394
107,924
Mean
0.56
0.47
0.87
0.67
10.71
2.97
46.62
0.54
0.51
0.11
9.84
0.03
Std. dev.
0.50
0.50
0.34
0.47
3.96
1.82
17.37
0.50
0.50
0.31
2.85
0.16
Presidential year (2008)
Obs.
80,667
12,021
59,775
150,799
110,237
150,799
100,008
105,869
132,812
101,534
105,869
105,416
Mean
0.74
0.45
0.84
0.64
10.89
2.97
46.95
0.54
0.51
0.1
9.95
0.04
Std. dev.
0.44
0.5
0.37
0.48
3.95
1.88
17.52
0.5
0.5
0.3
2.81
0.19
Congressional year (2010)
Obs.
79,819
15,125
44,625
152,162
134,179
152,162
101,750
107,494
134,179
103,259
107,494
107,082
Mean
0.56
0.5
0.83
0.63
10.63
2.99
47.27
0.53
0.51
0.1
10.01
0.05
Std. dev.
0.5
0.5
0.38
0.48
4.07
1.89
17.63
0.5
0.5
0.3
2.8
0.23
Presidential year (2012)
Obs.
82,820
12,544
59,364
151,598
133,427
151,598
102,011
107,315
133,427
103,328
107,315
106,871
Mean
0.72
0.47
0.82
0.62
10.81
2.97
47.68
0.53
0.51
0.09
10.14
0.04
Std. dev.
0.45
0.50
0.38
0.49
4.08
1.89
17.78
0.50
0.50
0.29
2.79
0.20
K. R. HUYSER ET AL.
Presidential year (2008)
Variable
Black
AI/AN
White
Hispanic
Years in home
Interviewer-self
Urban
126,950
126,950
126,950
126,950
91,858
94,013
153,255
0.10
0.01
0.76
0.13
4.97
0.57
0.77
0.30
0.10
0.43
0.34
1.40
0.49
0.42
123,666
123,666
123,666
123,666
83,035
83,835
150,799
0.1
0.01
0.75
0.13
5.1
0.6
0.77
0.31
0.1
0.43
0.34
1.34
0.49
0.42
124,714
124,714
124,714
124,714
80,684
81,950
152,162
0.11
0.01
0.74
0.14
5.13
0.6
0.77
0.31
0.1
0.44
0.35
1.34
0.49
0.42
123,614
123,614
123,614
123,614
83,288
85,673
151,598
0.11
0.01
0.74
0.14
5.15
0.57
0.78
0.31
0.10
0.44
0.35
1.33
0.49
0.41
Income (1 = Less than $5k, 2=$5k$–$7499, 3=$7500$–$9999, 4=$10,000–$12,499, 5=$12,500–$14,999, 6=$15,000–$19,999 7=$20,000–$24,999 8=$25,000–$29,999 9=$30,000–$34,999 10=
$35,000–$39,999 11=$40,000–$49,999 12=$50,000–$59,999 13=$60,000–$74,999 14=$75,000–$99,999 15=$100,000–$149,999 16=$150,000 or more).
b
Education (1 = Less than first grade, 2 = first, second, third, or fourth grade, 3 = fifth or sixth grade, 4 = seventh or eighth grade, 5 = ninth grade, 6 = 10th grade,7 = 11th grade, 8 = 12th grade-no
diploma ,9 = HS Grade or Equivalent, 10 = Some College, 11 = Associates Degree-Vocational, 12 = Associates Degree-Academic, 13 = Bachelor’s Degree, 14 = Master’s Degree, 15 = Professional
Degree,16 = Doctorate Degree).
POLITICS, GROUPS, AND IDENTITIES
Downloaded by [96.42.45.174] at 16:34 18 February 2016
a
9
10
K. R. HUYSER ET AL.
Table 2. Logistic regression predicting whether respondent contacted a public official, using CPS – civic
engagement supplement.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Presidential year (2008)
Congressional year (2010)
Variables
Full model
OR
AI/AN model
OR
Non-AI/AN model
OR
Full model
OR
AI/AN model
OR
Non-AI/AN model
OR
Homeowner
Income
Number in HH
Age
Marital status
Female
Veteran
Education
Unemployed
Black
AI/AN
Hispanic
Observations
1.22***
1.03***
0.94***
1.01***
1.18***
0.98
1.14**
1.25***
1.14
0.61***
1.09
0.53***
135,128
1.56
1.1
0.82
1.03**
2.29*
1.57
1.03
1.09
0.84
1.29***
1.03***
0.92***
1.01***
1.2***
0.98
1.15***
1.26***
1.13
1.01
1.01
0.78*
1.01
1.75*
0.97
0.72
1.13
0.63
1.47***
1.03***
0.91***
1.02***
1.23***
0.9***
1.14***
1.27***
1.27***
1101
110,942
1.37***
1.03***
0.93***
1.02***
1.21***
0.89***
1.12**
1.26***
1.3***
0.64***
1.31
0.5***
146,267
1131
122,335
*p < .1.
**p < .05.
***p < .01.
Table 3. Logistic regression predicting whether respondent boycotted, using CPS – civic engagement
supplement.
Presidential year (2008)
Congressional year (2010)
Variables
AI/AN model
OR
Non-AI/AN model
OR
AI/AN model
OR
Non-AI/AN model
OR
Homeowner
Income
Number in HH
Age
Marital status
Female
Veteran
Education
Unemployed
Observations
2.61*
0.94
0.62**
0.97
2.13
1.05
0.53
1.5***
2.19
1099
1.13***
1.07***
0.91***
1**
1.05
1.14***
1.06
1.25***
1.14
110,907
0.41**
1.04
0.9
0.99
2.04*
1.55
2.83
1.12
1.71
1134
1.07*
1.05***
0.88***
1***
1.17***
1.12***
1.15***
1.27***
1.27***
122,197
*p < .1.
**p < .05.
***p < .01.
(Table 3) than AI/ANs who are not married in both 2008 and 2010. In the 2008 model, we
find that AI/ANs who are older are more likely to contact a public official. Furthermore,
we find that as the number of AI/ANs in the household increases, respondents are less
likely to contact a public official or boycott. We find that education is positively correlated
with boycotting, but education is not statistically significant for our logistic regression predicting contacting a public official. In our non-AI/AN models in Tables 2 and 3, we find
that being a homeowner, having a higher income, being older in age, being female, being a
veteran, and having higher levels of education to be positively associated with contacting a
public official.
In Table 4, we present our findings for our negative binomial regression models that
predict the number of groups and/or organizations that the respondent participates in.
We again focus our attention on the AI/AN population. We find here that there are a
POLITICS, GROUPS, AND IDENTITIES
11
Table 4. Negative binomial regression – predicting groups/organizations that respondent participates,
using CPS – civic engagement supplement.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Presidential year (2008)
Congressional year (2010)
Variables
Full model
IRR
AI/AN model
IRR
Non-AI/AN model
IRR
Full model
IRR
AI/AN model
IRR
Non-AI/AN model
IRR
Homeowner
Income
Number in HH
Age
Marital status
Female
Veteran
Education
Unemployed
Black
AI/AN
Hispanic
Constant
Observations
1.21***
1.02***
1.1***
1***
1.21***
1.18***
1.1***
1.16***
1.06
0.95*
0.92
0.72***
0.04***
134,967
0.86
1.05
1.11
1
1.94***
1.27
1.68*
1.04
0.8
1.24***
1.02***
1.09***
1***
1.21***
1.19***
1.11***
1.17***
1.06***
1.02
0.98
0.97
1.01
2.1***
0.81
0.96
1.16***
0.76
1.26***
1.03***
1.07***
1.01***
1.24***
1.18***
1.18***
1.17***
1.06***
0.1***
1098
0.04***
110,784
1.23***
1.03***
1.08***
1.01***
1.25***
1.17***
1.17***
1.16***
1.07***
1.01***
0.89***
0.71***
0.03***
146,025
0.08***
1134
0.03***
122,090
*p < .1.
**p < .05.
***p < .01.
few key sociodemographic factors that are statistically significant in predicting participation in groups and/or organizations. Marital status for AI/ANs continues to predict
greater civic engagement (participation in groups and/or organizations), with married
respondents reporting greater participation levels in organizational involvement. In our
presidential year (2008), we find that AI/ANs who are veterans are more likely to participate in groups and/or organizations than non-veteran AI/ANs, but the statistical significance does not hold in a congressional year (2010). While specific to 2008, the higher rates
of organizational involvement support our hypothesis that military service facilitates
greater political participation among AI/ANs. Education also continues to remain relevant, as we find that AI/ANs with higher levels of education are more likely to engage
in groups and/or organizations. In the non-AI/AN negative binominal regression
models, we find that all of the respondent socioeconomic characteristics are associated
with participating in groups and/or organizations with the exception of employment
status in 2008. Therefore, we see that socioeconomic characteristics are much stronger
predictors of civic engagement for the non-AI/AN population than they are for our
target population. This is preliminary evidence supporting the notion that the unique
sovereign status of the AI/AN population has led to a different political socialization
process for this population than others more typically studied by political scientists.
Voting and registration results
We now turn our attention to the voter registration and voting models. In Table 5, we
present the results from our logistic regression model predicting voting. In the full
model of our presidential years (2008 and 2012), we see slightly different trends in AI/
AN voting. In 2008, we see that AI/ANs are significantly (27.9%) less likely to vote
than non-Hispanic whites when controlling for sociodemographic characteristics (OR =
0.721, p < .01). This supports earlier work suggesting that AI/ANs are less likely to vote
12
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Congressional year (2006)
Presidential year (2008)
Congressional year (2010)
Presidential year (2012)
Variables
Full model
OR
AI model
OR
Non-AI model
OR
Full model
OR
AI model
OR
Non-AI model
OR
Full model
OR
AI model
OR
Non-AI model
OR
Full model
OR
AI model
OR
Non-AI model
OR
Homeowner
Income
Number in HH
Age
Marital status
Female
Veteran
Education
Unemployed
Black
AI/AN
Hispanic
Years in home
Interviewer-self
Urban
Indian state
Constant
Observations
1.373***
1.056***
0.944***
1.031***
1.345***
1.074***
1.152***
1.257***
0.866**
1.454***
0.901
0.847***
1.264***
1.166***
0.918***
0.954***
0.004***
85,244
1.475
1.067**
0.876**
1.041***
1.292
1.081
0.961
1.134**
1.008
1.345***
1.052***
0.946***
1.031***
1.318***
1.079***
1.166***
1.258***
0.891*
0.734
1.093**
0.944
1.027**
2.085***
1.817**
1.301
1.137**
0.800
1.127***
1.059***
0.946***
1.017***
1.335***
1.343***
1.162***
1.322***
0.942
1.210***
1.044***
0.964***
1.031***
1.434***
1.047**
1.099***
1.249***
0.999
1.229***
1.047***
0.957***
1.021***
1.313***
1.261***
1.169***
1.311***
0.968
1.392***
1.234
1.607*
1.411
0.005***
579
1.189***
1.234***
1.259***
0.954**
0.012***
63,832
1.263***
0.934
0.649*
1.237
0.024***
664
1.261***
1.112***
1.036
1.046
0.004***
73,452
1.342***
1.056***
0.951***
1.022***
1.397***
1.255***
1.162***
1.318***
0.902**
2.800***
0.942
0.965
1.191***
1.169***
1.028
1.046
0.008***
96,069
1.762**
0.976
1.022
1.026***
1.374
1.110
0.891
1.272***
0.696
1.264***
1.166***
0.932**
0.925**
0.004***
67,307
1.265***
1.050***
0.958***
1.031***
1.483***
1.039**
1.090**
1.250***
0.978
1.820***
1.153
0.906***
1.260***
1.108***
1.005
1.078**
0.004***
92,130
1.136
1.102***
0.793***
1.026***
1.257
0.892
1.108
1.131**
0.755
1.319***
1.074
0.611*
1.357
0.005***
705
1.191***
1.072***
0.935***
1.017***
1.415***
1.342***
1.152***
1.322***
0.890**
2.624***
0.721***
0.889**
1.189***
1.233***
1.215***
1.011
0.009***
82,427
1.440***
1.032
1.375
0.852
0.005***
773
1.196***
1.167***
1.086***
1.002
0.010***
77,101
*p < .1.
**p < .05.
***p < .01.
K. R. HUYSER ET AL.
Table 5. Logistic regression – predicting voting, using CPS – November voting and registration supplement.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
POLITICS, GROUPS, AND IDENTITIES
13
than non-AI/ANs (Peterson 1997). However, in 2012, there is no statistical difference
between AI/ANs and non-Hispanic whites. Interestingly, in our congressional years of
2006 and 2010, when controlling for sociodemographic characteristics, we find that AI/
ANs are not statistically different from non-Hispanic whites, ceteris paribus. We interpret
this finding to suggest that AI/ANs are more engaged in local politics and are engaged in
voting behavior that aligns with tribal issues, as suggested in prior research.
In our AI/AN only models, we find slight differences in sociodemographic characteristics associated with voting in our presidential years compared to our congressional
years. Similar to the civic engagement models, we find the most association between sociodemographic characteristics and voting in our non-AI/AN models. We will first turn our
attention to the presidential years. In 2008, having a higher income, being older, being
married, being female, having higher education, higher number of years in home, and
living in an urban area are associated with an increased likelihood of voting that year
among AI/ANs. In 2012, we see fewer sociodemographic characteristics associated with
voting; we do see that homeownership, being older, having higher education, and
higher number of years in home are associated with an increased likelihood of voting.
In our congressional years, we have similar trends; higher income, being older, having
higher education and higher number of years in home continue to have a statistically significant association with voting. Singular to our congressional years, we find that a larger
household is negatively associated with voting; that is, individuals who report more people
in the household are less likely to vote. We also see that AI/ANs in urban areas are less
likely to vote than AI/ANs in rural areas in our congressional years, but urban AI/ANs
are more likely to vote in the presidential years. We interpret this finding to suggest
that AI/ANs who are invested into tribal politics are voting in congressional years, and
those less engaged in tribal politics are voting in presidential year.6 The literature on
voting discrimination in Indian states would suggest differential turnout in voting
between Indian states and non-Indian states; notably, we do not find statistical difference
between Indian states and non-Indian states in the majority of our AI/AN models.
Finally, we conducted a logistic regression predicting whether the respondent did
not register to vote because of lack of interest in politics, and our results are presented
on Table 6. In the full models, we find that the odds ratios for AI/ANs are not statistically
different from non-Hispanic whites except for Congressional year 2006. In 2006, AI/ANs
are 29.7% less likely not to register to vote because of lack of interest in politics than nonHispanic whites (OR = 0.703, p < .01), which may also suggest the importance of tribal
issues in Congressional voting behavior for AI/ANs. Examining our odds ratios for
Blacks and Hispanics in both the presidential and congressional year, we find that they
are lower odds of not being registered to vote because of lack of interest in politics than
non-Hispanic whites. In our stratified AI/AN model, we have only a few sociodemographic characteristics associated with not being registered to vote because of lack of interest in politics, which may be due to sample size. Overall, we find that AI/ANs with lower
levels of education and being younger are associated with not being registered to vote
because of lack of interest in politics.7
When we summarize the overall voting analysis results, we find that socioeconomic
indicators (income, age, marital status, gender, education, and residential stability) are
important predictors for voting among the AI/AN population, which is consistent with
the broader literature on political participation (Conner 2014; Peterson 1997; Verba,
14
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Congressional year (2006)
Variables
Homeowner
Income
Number in HH
Age
Marital status
Female
Veteran
Education
Unemployed
Black
AI/AN
Hispanic
Years in home
Interviewer-self
Urban
Indian state
Constant
Observations
*p < .1.
**p < .05.
***p < .01.
Presidential year (2008)
Congressional year (2010)
Full model
OR
AI model
OR
Non-AI model
OR
Full model
OR
AI model
OR
Non-AI model
OR
Full model
OR
0.935
0.992
0.992
0.992***
1.133***
0.977
0.979
0.943***
1.215**
0.687***
0.703*
0.689***
1.200***
1.077*
0.878***
1.218***
1.188
30,560
1.368
0.932
0.801**
0.982
1.295
1.212
5.869**
0.985
0.992
0.969
0.998
0.977
0.992***
1.141***
0.982
0.975
0.948***
1.191*
1.026
1.066
1.115
0.980
1.210
0.969
1.527
0.777*
0.874
1.191***
0.990
0.931***
0.996**
1.207***
1.033
1.213**
0.993
1.365***
1.118
0.714
0.663
1.383
3.113
181
1.200***
1.073
0.823***
1.181**
1.034
13,147
1.162**
0.983**
0.946***
0.995***
1.210***
1.027
1.194*
0.986
1.356***
0.676***
1.255
0.704***
1.107***
0.912*
0.678***
1.087
1.200
27,744
1.242
0.357**
0.468
1.197
9.115
142
1.103***
0.916*
0.652***
1.047
1.013
9586
0.925
0.988**
0.952***
0.990***
1.213***
0.990
0.973
0.957***
1.123
0.644***
0.892
0.730***
1.231***
1.061
0.836***
1.095
1.359**
32,057
AI model
OR
Presidential year (2012)
Non-AI model
OR
Full model
OR
AI model
OR
Non-AI model
OR
1.097
1.092
0.860
0.982
1.398
0.633
3.746
1.021
1.385
0.966
0.990*
0.941***
0.990***
1.224***
0.991
0.977
0.962***
1.106
0.496
0.972
0.927
0.950***
1.373
0.665
4.822
0.955
3.455
0.983
1.007
1.011
0.997**
1.176***
0.959
1.057
0.996
1.063
1.420**
2.015
0.689
3.190***
0.152
188
1.225***
1.047
0.793***
1.052
1.212
13,855
0.924
1.000
1.028*
0.995***
1.178***
0.948
1.044
0.988
1.080
0.575***
1.127
0.615***
1.148***
1.048
0.798***
0.841**
0.779
29,975
1.577***
1.129
1.324
0.178***
5.040
176
1.139***
1.040
0.731***
0.843**
0.632***
11,604
K. R. HUYSER ET AL.
Table 6. Logistic regression – predicting not registering to vote because not interested in politics, using CPS – November voting and registration supplement.
POLITICS, GROUPS, AND IDENTITIES
15
Scholzman, and Brady 1995). For example, in the 2008 registration models, we found that
individuals with lower levels of education and AI/ANs who are younger were less likely to
register to vote which is in line with decades of research in this area on the more general
population.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Conclusion
Native voters are an important yet often overlooked electorate in the US. AI/ANs may participate in political and civic engagement activities to protect and defend sovereignty rights
(Kahn 2013), and this legal and cultural backdrop may encourage AI/AN individuals to
play apart in more local events and politics. However, AI/AN populations may have
lower political mobilization due to a lack of social cohesion that is a result of diverse
tribal affiliations and geographic dispersion (Luna 2000). Our paper provides a snapshot
into understanding civic engagement and political participation among AI/ANs using the
CPS Civic Engagement and Voting and Registration supplements.
The major goal of our project was to compare the levels of political participation and
civic engagement more broadly for AI/ANs relative to non-AI/ANs as well as to examine
whether the contributing factors to political participation vary in meaningful ways for the
AI/AN population. In short, we found that the AI/AN population was significantly less
likely to vote during the 2008 election than the non-AI/AN population but no more or
less likely to vote in any other year. This may suggest that AI/ANs are interested in
more local politics and voting for representatives who will represent their tribal interests
in national politics, and emphasizes the value of including both presidential and non-presidential elections in analysis of AI/AN voting trends. We also find some variation in our
results dependent on election type. For example, AI/AN veterans are statistically more
likely to participate in groups and/or organizations during the presidential election; yet,
there is no statistical significance during the congressional year.
When we look at civic engagement more broadly, we find that AI/ANs are considerably
more involved in 2010 than in 2008. More specifically, we find that the AI/AN population
is more likely to contact a public official in both 2008 and 2010 than non-Hispanic whites,
and AI/ANs are not statistically different from non-Hispanic whites when it comes to
involvement in groups and/or organizations. Although not consistently statistically significant across all types of civic engagement, we find marital status, age, household size, education, and veteran status to be important in predicting civic engagement.
We find mixed results for our inquiry into whether or not the variables that predict political participation vary significantly for the AI/AN population. We do see that the models
focused on sociodemographic factors do a much better job of explaining the political participation rates of non-Native populations, as there are many more statistically significant
variables in those models than those stratified specific to the AI/AN population. This may
be partially due to the overall lower socioeconomic status (lower education and income
levels compared to non-Hispanic whites) and higher rates of poverty experienced by
many AI/ANs (Huyser, Sakamoto, and Takei 2010; Huyser, Takei, and Sakamoto 2014).
That said, we see that many of the socioeconomic variables commonly identified in political participation models for the more general population are relevant to the AI/AN
population (Min and Savage 2014; Skopek and Garner 2014). For example, being
married, having higher education levels, and household size are important predictors of
Downloaded by [96.42.45.174] at 16:34 18 February 2016
16
K. R. HUYSER ET AL.
political participation for AI/ANs. This is similar to what we see in the more general population. One consistently important socioeconomic status indicator in predicting civic and
political engagement was that AI/ANs who resided in larger households were less likely to
be engaged. Considering that AI/AN households tend to be larger than non-AI/AN households (Snipp 1989), it is important for us to broaden our concept of resources within
socioeconomic attainment to understand what is needed to be both politically and civically
active.
While we believe that this study helps to inform the extant knowledge of AI/AN political participation, our study has a few limitations that we hope our team and others will
work to address in the future. Although we are using the CPS supplements on Civic
Engagement and Voting and Registration, and it provides a national sample of AI/ANs,
it does not collect information on particular local activities, including engagement in
tribal elections. It also does not ask the respondents about tribal affiliation; thus, we are
unable to examine engagement in tribal politics or whether there is meaningful variation
across tribal communities. This is vital, as knowing whether participation in tribal elections influences civic engagement more broadly is a fascinating question that should be
addressed when data are available to do so. Similarly, expanding the group identity literature to assess how group consciousness among Native Americans influences political
engagement would be a major advancement to that body of work. Having a sense of
how variation in tribal and clan identity influences civic engagement, and, more minimally, tribal affiliation, would be of interest to a wide group of scholars beyond racial
and ethnic politics. Finally, direct analysis of how felony disenfranchisement laws may
impact the voting power of the AI/AN population should be conducted in the future.
Given that the Native American population has incarceration rates twice that of the
white population in the US, these laws likely have a significant impact on the political
engagement of the population.8
There is clearly a need for a national survey of AI/ANs that addresses these limitations
as well as non-socioeconomic contributors to participation such as political knowledge
and political mobilization. Despite these limitations, we believe our study contributes
an important glimpse into understanding civic and political engagement among AI/
ANs. It is our hope that this study helps to build momentum toward more work in this
area, as many of the suggestions for future research would not only inform our knowledge
of the Native American community but American democracy more broadly.
Notes
1. http://indiancountrytodaymedianetwork.com/2012/11/01/elections-2012-native-americanshave-more-influence-new-mexico-any-other-state-143397.
2. See Rosenstone and Hansen (1993) for a discussion of how voter suppression negatively
impacted the participation rates of African Americans.
3. https://www.aclu.org/files/pdfs/votingrights/indiancountryreport.pdf.
4. http://indiancountrytodaymedianetwork.com/2014/07/11/got-tribal-id-north-dakota-nativesmay-not-be-able-use-theirs-vote-155776.
5. We also ran models using region controls and compared the results to the Indian state control
models. Overall, we found similar findings and felt that the Indian state control models have
used more theoretically meaningful results.
6. Since AI/ANs in Alaska may experience different political, physical, and linguistic environment
than AI/ANs in the contiguous US, we also ran our voting models for only Alaska. Due to small
POLITICS, GROUPS, AND IDENTITIES
17
sample sizes, the analysis can only suggest trends for the AI/AN only models. In general, for AI/
ANs in Alaska, AI/ANs who are female, own a home, have higher income and education are
more likely to vote.
7. We also ran logistic regression predicting whether the respondent did not register to vote
because of lack of interest in politics for Alaska, and our sample size was too small to create estimates for AI/ANs or Blacks.
8. http://www.nccdglobal.org/sites/default/files/publication_pdf/created-equal.pdf.
Disclosure statement
No potential conflict of interest was reported by the authors.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
Funding
This work was supported by the Russell Sage Foundation. We would like to thank the Robert Wood
Johnson Foundation Center for Health Policy at the University of New Mexico for excellent
research support. Edward D. Vargas was supported by a NICHD training grant to the University
of Wisconsin-Madison (T32HD049302). The content is solely the responsibility of the authors
and does not necessarily represent the official views of the Eunice Kennedy Shriver National Institute of Child Health and Human Development or the National Institutes of Health.
References
Beltran, Christina. 2010. The Trouble with Unity: Latino Politics and the Creation of Identity.
Oxford: University Press.
Brady, Henry E., Sidney Verba, and Kay Lehman Schlozman. 1995. “Beyond SES: A Resource
Model of Political Participation.” The American Political Science Review 89 (2): 271–294.
Conner, Thaddieus W. 2014. “Exploring Voting Behavior on American Indian Legislation in the
United States Congress.” The Social Science Journal 51 (2): 159–166. doi:10.1016/j.soscij.2014.
01.002
Corntassel, Jeff J., and Richard C. Witmer II. 1997. “American Indian Tribal Government Support
of Office-Seekers: Findings from the 1994 Election.” The Social Science Journal 34 (4): 511–525.
Dawson, Michael C. 1994. Behind the Mule: Race, Class and African American Politics. Princeton,
NJ: Princeton University Press.
Department of Defense. 2013. “Demographics 2013 – Profile of the Military Community.” Office of
the Deputy Under Secretary of Defense. Military Community and Family Policy.
Holiday, L. F., G. Bell, R. E. Klein, and M. R. Wells. 2006. American Indian and Alaska Native
Veterans: Lasting Contributions. Washington, DC: U.S. Department of Veteran Affairs, Office
of Policy Assistant Secretary for Policy, Planning, and Preparedness.
Huyser, K. R., Arthur Sakamoto, and Isao Takei. 2010. “The Persistence of Racial Disadvantage: The
Socioeconomic Attainments of Single-Race and Multi-Race Native Americans.” Population
Research and Policy Review 29: 541–568.
Huyser, Kimberly R., Isao Takei, and Arthur Sakamoto. 2014. “Demographic Factors Associated
with Poverty Among American Indians and Alaska Natives.” Race and Social Problems 6 (2):
120–134.
Indian Citizenship Act of 1924, Pub. L. 68-175, 43 Stat. 253.
Kahn, Benjamin A. 2013. “A Place Called Home: Native Sovereignty Through Statehood and
Political Participation.” Natural Resources Journal 53: 1–53.
Leighley, Jan E. 2001. Strength in Numbers? The Political Mobilization of Racial and Ethnic
Minorities. Princeton, NJ: Princeton University Press.
Leighley, Jan E., and Arnold Vedlitz. 1999. “Race, Ethnicity, and Political Participation: Competing
Models and Contrasting Explanations.” The Journal of Politics 61 (4): 1092–1114.
Downloaded by [96.42.45.174] at 16:34 18 February 2016
18
K. R. HUYSER ET AL.
Luna, Eileen M. 2000. “Mobilizing the Unrepresented: Indian Voting Patterns and the Implications
for Tribal Sovereignty.” Wicazo Sa Review 15: 91–115.
McCool, Daniel, Susan M. Olson, and Jennifer L. Robinson. 2007. Native Vote: American Indians,
the Voting Rights Act, and the Right to Vote. Cambridge: Cambridge University Press.
Min, Tae Eun. 2014. “The Impact of Panethnicity on Asian American and Latino Political
Participation.” Ethnicities 14 (5): 698–721.
Min, Jeonghun, and Daniel Savage. 2014. “Why do American Indians Vote Democratic?” The Social
Science Journal 51 (2): 167–180.
Peterson, Helen L. 1957. “American Indian Political Participation.” Annals of the American
Academy of Political and Social Science 311 (1): 116–126.
Peterson, Geoff. 1997. “Native American Turnout in the 1990 and 1992 Elections.” American
Indian Quarterly 21 (2): 321–331.
Rosenstone, Steven J., and John Mark Hansen. 1993. Mobilization, Participation, and Democracy.
New York: Macmillan.
Sanchez, Gabriel. 2006. “The Role of Group Consciousness in Political Participation Among
Latinos in the United States.” American Politics Research 34 (4): 427–450.
Sandefur, Gary D., and Trudy McKinnell. 1986. “American Indian Intermarriage.” Social Science
Research 15 (4): 347–371.
Sells, Bryan L. 2012. “The Voting Rights Act in South Dakota: One Litigator’s Perspective on
Reauthorization.” In The Most Fundamental Right Contrasting Perspectives on the Voting
Rights Act, edited by Daniel McCool, 157–187. Bloomington: Indiana University Press.
Skopek, Tracy, and Andrew Garner. 2014. “The Disappearing Turnout Gap between Native
Americans and Non-Native Americans.” American Indian Culture and Research Journal 38
(2): 1–16.
Snipp, C. Matthew. 1989. American Indians: The First of this Land. New York: Russell Sage
Foundation.
StataCorp. 2011. Stata Statistical Software: Release 12. College Station, TX: StataCorp LP.
U.S. Census Bureau. 2009a. CPS 2008 Civic Engagement Supplement File Technical Documentation.
Washington, DC: Bureau of Labor Statistics and Bureau of the Census.
U.S. Census Bureau. 2009b. CPS 2008 Voting and Registration Supplement File Technical
Documentation. Washington, DC: Bureau of Labor Statistics and Bureau of the Census.
U.S. Census Bureau. 2010a. “Current Population Survey, November 2010: Civic Engagement
Supplement [Computer file].” ICPSR32341-v1. Ann Arbor, MI: Inter-university Consortium
for Political and Social Research [distributor], 2011-12-16. doi:10.3886/ICPSR32341.v1
U.S. Census Bureau. 2010b. “Current Population Survey, November 2010: Voting and Registration
Supplement [Computer file].” ICPSR31082-v1. Ann Arbor, MI: Inter-university Consortium for
Political and Social Research [distributor], 2011-07-14. doi:10.3886/ICPSR31082.v1
Verba, Sidney, Kay Lehman Scholzman and Henry E. Brady. 1995. Voice and Quality: Civic
Voluntarism in American Politics. Cambridge, MA: Harvard University Press.
Witmer, Richard C., Joshua Johnson, and Frederick J. Boehmke. 2014. “American Indian Policy in
the States.” Social Science Quarterly 95 (4): 1043–1063.
Wong, Janelle S., Pei-Te Lien, and Margaret Conway. 2005. “Group-based Resources and Political
Participation among Asian Americans.” American Politics Research 33 (4): 545–576.